1. Field of the Invention
This invention relates generally to the field of semiconductor device manufacturing and, more particularly, to a method and apparatus for coordinating fault detection settings and process control changes.
2. Description of the Related Art
There is a constant drive within the semiconductor industry to increase the quality, reliability and throughput of integrated circuit devices, e.g., microprocessors, memory devices, and the like. This drive is fueled by consumer demands for higher quality computers and electronic devices that operate more reliably. These demands have resulted in a continual improvement in the manufacture of semiconductor devices, e.g., transistors, as well as in the manufacture of integrated circuit devices incorporating such transistors. Additionally, reducing the defects in the manufacture of the components of a typical transistor also lowers the overall cost per transistor as well as the cost of integrated circuit devices incorporating such transistors.
Generally, a set of processing steps is performed on a lot of wafers using a variety of processing tools, including photolithography steppers, etch tools, deposition tools, polishing tools, rapid thermal processing tools, implantation tools, etc. The technologies underlying semiconductor processing tools have attracted increased attention over the last several years, resulting in substantial refinements. However, despite the advances made in this area, many of the processing tools that are currently commercially available suffer certain deficiencies. In particular, such tools often lack advanced process data monitoring capabilities, such as the ability to provide historical parametric data in a user-friendly format, as well as event logging, real-time graphical display of both current processing parameters and the processing parameters of the entire run, and remote, i.e., local site and worldwide, monitoring. These deficiencies can engender non-optimal control of critical processing parameters, such as throughput, accuracy, stability and repeatability, processing temperatures, mechanical tool parameters, and the like. This variability manifests itself as within-run disparities, run-to-run disparities and tool-to-tool disparities that can propagate into deviations in product quality and performance, whereas an ideal monitoring and diagnostics system for such tools would provide a means of monitoring this variability, as well as providing means for optimizing control of critical parameters.
One technique for improving the operation of a semiconductor processing line includes using a factory wide control system to automatically control the operation of the various processing tools. The manufacturing tools communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface that facilitates communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script based upon a manufacturing model, which can be a software program that automatically retrieves the data needed to execute a manufacturing process. The control script generates control actions for making process control adjustments to the process to reduce variation in the processed devices with respect to a desired target value.
Data gathered during the course of wafer processing is used to identify and attempt to mitigate the effects of process and equipment variations by implementing automatic control techniques (i.e., process control) and/or automatic fault detection and classification (FDC) techniques based on the collected data.
Fault detection analysis may be conducted on metrology data collected for the processed wafers to determine if the device characteristics are within acceptable ranges. For example, if the dimensions of a particular feature are outside an acceptable range, the wafer may be either reworked or scrapped. Fault detection is also performed on data collected during the processing runs of the tools used to process the wafers. The data may be supplied by the tools, sensors associated with the tools, and/or process controllers controlling the tools.
The health of a tool may be determined by employing a multivariate tool health model adapted to predict the expected operating parameters of the tool during the processing run. If the actual observed tool parameters are close to the predicted tool parameters, the tool is said to have a high health metric (i.e., the tool is operating as expected). As the gap between the expected tool parameters and the observed tool parameters widens, the tool health metric decreases. An exemplary tool health monitor software application is ModelWare™ offered by Triant, Inc. of Nanaimo, British Columbia, Canada Vancouver, Canada. An exemplary system for monitoring tool health is described in U.S. patent application Ser. No. 09/863,822, entitled “METHOD AND APPARATUS FOR MONITORING TOOL HEALTH,” filed in the names of Elfido Coss Jr., Richard J. Markle, and Patrick M. Cowan, that is assigned to the assignee of the present application and incorporated herein by reference in its entirety.
In some cases, where a high degree of oversight is desired for a particular tool or product (e.g., for processing a high grade device), the thresholds for determining fault conditions are set to indicate a fault condition for even slight deviations from expected values. In response to a fault condition, a particular tool may be automatically shut down to avoid producing subsequent faulty wafers.
Process control actions typically result in shifting one or more operating parameters of a tool to reduce variation on the wafers processed by the tool. These intentional shifts also cause shifts in the data collected for analyzing the tool health. The tools health monitoring applications do not expect such a shift and may erroneously indicate a fault condition with the tool upon observing the shift. Accordingly, the tool may be automatically shut down by the FDC system and production time may be lost. Operator or engineering intervention is typically required to determine that no fault condition actually exists and to reset the tool health model and associated FDC limits. Unnecessary tool shutdowns consume valuable processing and engineering time and may reduce the profitability of the fabrication facility.
The present invention is directed to overcoming, or at least reducing the effects of, one or more of the problems set forth above.